A SINR Maximizing Interpolation-and-Decimation-based Dimensionality Reduction Technique, with Application to Beamforming

Abstract

We present a dimensionality reduction technique based on a joint interpolation and decimation scheme, with application to beamforming. The dimensionality reduction is achieved by a two step procedure: interpolation followed by decimation. The array snapshots are interpolated by a finite impulse response (FIR) filter in order to generate correlation between its samples. The decimation stage then discards some samples from the correlated interpolator output signal, effectively reducing the snapshots’ length. A notable point of this technique is the elegant and effective way to design the interpolation filter. The design is such that, for a given decimation pattern, the interpolation filter maximizes the signal-to-interference-and-noise ratio (SINR) at the ouput of the decimation stage. The optimization of the reduced dimensionality stage is made independently of the final application filtering stage, allowing the proposed scheme to be combined with any interference-suppressive or detection filter of choice. Investigation of this technique in light of the particularities of the beamforming signal model led to, here proposed, simplifications that allowed for a significant reduction of its overall complexity. Comparison with renowned robust rank reduction techniques show that the proposed approach has an excellent SINR loss figure of merit performance with superior robustness and low computational complexity.